CONSIDERACIONES PARA LA ADAPTACIÓN DEL ALGORITMO

This phase (Dror, 1973, Phase 12, Optimal Model) must meet two requirements to be optimal. First, the basic strategy choice between more innovative alternatives and more reliable predictions of benefits and costs (the more ‘radical’ approach and the more ‘conservative’ approach, respectively) should be made explicitly. Second, whatever strategy has been adopted, policymakers should try to construct as reliable a set of predictions as they can, within the limits set by economical allocation of resources, even if the predictions cannot be very reliable in any case. It should include four main sub elements for each alternative:

1. The foreseeable benefits and costs;

2. An indication of how valid are those predictions;

3. An indication of how probable it is that unpredictable

consequences will occur;

4. A clear demarcation of the cut-off horizon.

This is an area in which significant advances have been made in the decision sciences, for example in developing methods for better predicting of results of research and development. These advances can be used to reduce uncertainly in policymaking, after suitable adjustments have been made to them (Glenman, 1965, cited in Thomas K.G. Jr., 1965, p. 184). The most important rational techniques for reducing uncertainly about prediction sets include the following:

1. Theoretical analysis leads to prediction by way of a theoretical

understanding of the involved phenomena. In essence, such analysis requires a behavioural model of the involved phenomena, which can be qualitative (‘theory’), quasi-quantitative, or sometimes quantitative (as in econometrics). These models allow

simulation of the alternative policies and lead to predictions whose validity depends on the quality and validity of the models.

2. Extrapolation from the past, insofar as conditions are similar

enough that differences can be compensated for and insofar as the alternatives are conservative, is a usable basis for prediction, even when the involved phenomena are not understood, in which case their future states cannot be predicted by analysis.

3. Focused research is a powerful tool for reducing uncertainty,

though it is often time-consuming. It may be directed at providing data and knowledge that will allow the other techniques to be used. It may also be directly aimed at providing predictions, as in collating intelligence about international relations, or in public- opinion research about public reactions.

4. Pilot testing alternative policies is always hard and often

impossible but in many more situations than in which it has been used, it is the only feasible way to arrive at reasonably reliable predictions, particularly for complex, basic social issues where the time needed is available. Among such issues are birth control, housing patterns and traffic-control systems. Gaming belongs have as a weak form of pilot testing by analogy.

5. In sequential decision making, parallel approaches are adopted for

as long as significant learning from them takes place. This is both a technique for reducing uncertainty that could be used as a component of this phase, and a basic strategy for dealing with uncertainly that could be set down in phase 7 (determining policymaking strategy).

6. An important method for making predictions that illustrates the

possibilities for systematically using extra rational processes by means of explicit rational arrangements is by canvassing the intuition opinions and tacit knowledge of experts.

Phase 15: Motivating the execution of the policy

Motivating the execution of the policy is an essential post-policymaking action (Dror, 1973, Phase 15, Optimal Model). Since public policymaking is action-oriented, that is, since policies are intended to be executed, the probability that an alternative will receive the motivation it needs to be executed is one of its most important outputs and must be predicted when the alternative is evaluated during phase 12.

Phase 18: Communication and feedback channels inter- connecting all phases

This phase (Dror, 1973, Phase 18, Optimal Model) crosscuts and interconnects all the other phases, in terms of the conclusions and feedback resulting from it, which include: (1) immediate feedback about policy that is being executed and which is aimed at stimulating remarking of the policy; (2) immediate feedback about the policy that is being executed aimed and which is at stimulating changes in the way the policy is being executed, and (3) learning feedback, which is aimed at all the metapolicymaking, policymaking, and post-policymaking phases and intended to improve their future operation in the light of current experience. Since all these phases are dynamically interdependent and since most of them take place at the same time, policymaking must have highly elaborate and efficient communication and feedback channels and mechanisms in order to operate, especially to operate optimally.

The Dror Optimal Model provides valuable guidance by providing a framework that will be used to draw up a policy to improve the skills and for all the District Directors that might benefit the BMA in the future.

Summary

The selective review of the literature presented in this chapter was used to formulate the theoretical framework for this study. It has focused on (a) learning organisation, (b) professional development (c) program evaluation (d) qualitative data analysis and (d) policymaking.

Throughout the literature review, reference is made to the learning skills and competency needs of District Directors in the BMA. This study, ultimately addresses professional strategies for them to identify – by Delphi survey and semi-structured interviews – their needs in order to promote individual and team change that will ultimately have a beneficial effect on the BMA. Appropriate instruments for the comprehensive and integrative identification of skills and competencies needed and the professional development strategy across the professional life span have been identified are. Finally, the basis for the development of a professional development training policy that will bring these elements together has been described.

A fully-developed methodology that has been derived from this literature is presented in Chapter Three.